Desvio Percentual dos Carregamentos

Dataset statistics

Number of variables	22
Number of observations	45215
Missing cells	136534
Missing cells (%)	13.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.6 MiB
Average record size in memory	176.0 B

Variable types

Categorical	7
Numeric	8
DateTime	7

Alerts

`Matricula` has a high cardinality: 1822 distinct values	High cardinality
`NomeMotorista` has a high cardinality: 2695 distinct values	High cardinality
`Tara` is highly correlated with `bruto`	High correlation
`bruto` is highly correlated with `Tara` and 2 other fields	High correlation
`Liquido` is highly correlated with `bruto` and 1 other fields	High correlation
`qtdpedida` is highly correlated with `bruto` and 1 other fields	High correlation
`Tara` is highly correlated with `bruto`	High correlation
`bruto` is highly correlated with `Tara` and 2 other fields	High correlation
`Liquido` is highly correlated with `bruto` and 1 other fields	High correlation
`qtdpedida` is highly correlated with `bruto` and 1 other fields	High correlation
`Tara` is highly correlated with `bruto`	High correlation
`bruto` is highly correlated with `Tara` and 1 other fields	High correlation
`Liquido` is highly correlated with `qtdpedida` and 1 other fields	High correlation
`qtdpedida` is highly correlated with `bruto` and 1 other fields	High correlation
`percDiff` is highly correlated with `Liquido`	High correlation
`DescProduto` is highly correlated with `TipoViatura`	High correlation
`TipoViatura` is highly correlated with `DescProduto` and 1 other fields	High correlation
`PostoOperacao` is highly correlated with `TipoViatura`	High correlation
`TipoDoc` is highly correlated with `Tara` and 3 other fields	High correlation
`TipoViatura` is highly correlated with `DescProduto` and 1 other fields	High correlation
`CodProduto` is highly correlated with `DescProduto` and 3 other fields	High correlation
`DescProduto` is highly correlated with `TipoViatura` and 5 other fields	High correlation
`Tara` is highly correlated with `TipoDoc` and 4 other fields	High correlation
`bruto` is highly correlated with `TipoDoc` and 7 other fields	High correlation
`Liquido` is highly correlated with `CodProduto` and 4 other fields	High correlation
`qtdpedida` is highly correlated with `TipoDoc` and 5 other fields	High correlation
`percDiff` is highly correlated with `TipoDoc` and 2 other fields	High correlation
`PostoOperacao` is highly correlated with `TipoViatura` and 1 other fields	High correlation
`CodMotorista` is highly correlated with `bruto`	High correlation
`PostoOperacao` has 16288 (36.0%) missing values	Missing
`TaraData` has 26694 (59.0%) missing values	Missing
`DataInicioOperacao` has 26694 (59.0%) missing values	Missing
`DataFimOperacao` has 31522 (69.7%) missing values	Missing
`CodMotorista` has 35326 (78.1%) missing values	Missing
`DataCriacao` has unique values	Unique
`Dataentrada` has unique values	Unique
`percDiff` has 760 (1.7%) zeros	Zeros

Reproduction

Analysis started	2022-05-13 16:01:56.616308
Analysis finished	2022-05-13 16:02:12.930948
Duration	16.31 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

TipoDoc
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

TP	45055
SP	160

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	90430
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	TP
2nd row	TP
3rd row	TP
4th row	TP
5th row	TP

Common Values

Value	Count	Frequency (%)
TP	45055	99.6%
SP	160	0.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
tp	45055	99.6%
sp	160	0.4%

Most occurring characters

Value	Count	Frequency (%)
P	45215	50.0%
T	45055	49.8%
S	160	0.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	90430	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
P	45215	50.0%
T	45055	49.8%
S	160	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	90430	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
P	45215	50.0%
T	45055	49.8%
S	160	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	90430	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
P	45215	50.0%
T	45055	49.8%
S	160	0.2%

TipoViatura
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

Z002	28227
Z004	16988

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	180860
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Z004
2nd row	Z002
3rd row	Z002
4th row	Z002
5th row	Z004

Common Values

Value	Count	Frequency (%)
Z002	28227	62.4%
Z004	16988	37.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
z002	28227	62.4%
z004	16988	37.6%

Most occurring characters

Value	Count	Frequency (%)
0	90430	50.0%
Z	45215	25.0%
2	28227	15.6%
4	16988	9.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	135645	75.0%
Uppercase Letter	45215	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	90430	66.7%
2	28227	20.8%
4	16988	12.5%

Uppercase Letter

Value	Count	Frequency (%)
Z	45215	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	135645	75.0%
Latin	45215	25.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	90430	66.7%
2	28227	20.8%
4	16988	12.5%

Latin

Value	Count	Frequency (%)
Z	45215	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	180860	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	90430	50.0%
Z	45215	25.0%
2	28227	15.6%
4	16988	9.4%

CodProduto
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.545947141

Minimum	2
Maximum	42
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	2
5-th percentile	2
Q1	2
median	3
Q3	5
95-th percentile	37
Maximum	42
Range	40
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	8.446174665
Coefficient of variation (CV)	1.522945396
Kurtosis	12.83874307
Mean	5.545947141
Median Absolute Deviation (MAD)	1
Skewness	3.779239051
Sum	250760
Variance	71.33786648
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
3	14463	32.0%
5	14237	31.5%
2	12276	27.2%
42	1129	2.5%
6	967	2.1%
40	871	1.9%
11	450	1.0%
37	429	0.9%
7	393	0.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	12276	27.2%
3	14463	32.0%
5	14237	31.5%
6	967	2.1%
7	393	0.9%
11	450	1.0%
37	429	0.9%
40	871	1.9%
42	1129	2.5%

Value	Count	Frequency (%)
42	1129	2.5%
40	871	1.9%
37	429	0.9%
11	450	1.0%
7	393	0.9%
6	967	2.1%
5	14237	31.5%
3	14463	32.0%
2	12276	27.2%

DescProduto
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	1
Missing (%)	< 0.1%
Memory size	353.4 KiB

CIMENT II/AL 32,5 R PALETTE	14463
CIMENT I 42,5 R SAC	14237
CIMENT II/AL 32,5 R SAC	12276
CIMENT I 42,5 R SR3 PALETTE	1128
CIMENT I 42,5 R PALETTE	967
Other values (4)	2143

Length

Max length	28
Median length	27
Mean length	23.08342549
Min length	17

Characters and Unicode

Total characters	1043694
Distinct characters	23
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	CIMENT II/AL 32,5 R PALETTE
2nd row	CIMENT I 42,5 R SAC
3rd row	CIMENT I 42,5 R SAC
4th row	CIMENT I 42,5 R SAC
5th row	CIMENT I 42,5 R SR3 PALETTE

Common Values

Value	Count	Frequency (%)
CIMENT II/AL 32,5 R PALETTE	14463	32.0%
CIMENT I 42,5 R SAC	14237	31.5%
CIMENT II/AL 32,5 R SAC	12276	27.2%
CIMENT I 42,5 R SR3 PALETTE	1128	2.5%
CIMENT I 42,5 R PALETTE	967	2.1%
CIMENT II/AL 42,5 N SAC	871	1.9%
CHAUX CHA 10 SAC	450	1.0%
CHAUX CHA 10 PALETTE	429	0.9%
CIMENT I 42,5 R SR3 SAC	393	0.9%
(Missing)	1	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
ciment	44335	19.6%
r	43464	19.2%
sac	28227	12.5%
ii/al	27610	12.2%
32,5	26739	11.8%
42,5	17596	7.8%
palette	16987	7.5%
i	16725	7.4%
sr3	1521	0.7%
chaux	879	0.4%
Other values (3)	2629	1.2%

Most occurring characters

Value	Count	Frequency (%)
	184291	17.7%
I	116280	11.1%
E	78309	7.5%
T	78309	7.5%
A	74582	7.1%
C	74320	7.1%
N	45206	4.3%
R	44985	4.3%
L	44597	4.3%
5	44335	4.2%
Other values (13)	258480	24.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	651174	62.4%
Space Separator	184291	17.7%
Decimal Number	136284	13.1%
Other Punctuation	71945	6.9%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	116280	17.9%
E	78309	12.0%
T	78309	12.0%
A	74582	11.5%
C	74320	11.4%
N	45206	6.9%
R	44985	6.9%
L	44597	6.8%
M	44335	6.8%
S	29748	4.6%
Other values (4)	20503	3.1%

Decimal Number

Value	Count	Frequency (%)
5	44335	32.5%
2	44335	32.5%
3	28260	20.7%
4	17596	12.9%
1	879	0.6%
0	879	0.6%

Other Punctuation

Value	Count	Frequency (%)
,	44335	61.6%
/	27610	38.4%

Space Separator

Value	Count	Frequency (%)
	184291	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	651174	62.4%
Common	392520	37.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
I	116280	17.9%
E	78309	12.0%
T	78309	12.0%
A	74582	11.5%
C	74320	11.4%
N	45206	6.9%
R	44985	6.9%
L	44597	6.8%
M	44335	6.8%
S	29748	4.6%
Other values (4)	20503	3.1%

Common

Value	Count	Frequency (%)
	184291	47.0%
5	44335	11.3%
,	44335	11.3%
2	44335	11.3%
3	28260	7.2%
/	27610	7.0%
4	17596	4.5%
1	879	0.2%
0	879	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1043694	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	184291	17.7%
I	116280	11.1%
E	78309	7.5%
T	78309	7.5%
A	74582	7.1%
C	74320	7.1%
N	45206	4.3%
R	44985	4.3%
L	44597	4.3%
5	44335	4.2%
Other values (13)	258480	24.8%

estado
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

F	45201
C	14

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45215
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	F
2nd row	F
3rd row	F
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	45201	> 99.9%
C	14	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
f	45201	> 99.9%
c	14	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
F	45201	> 99.9%
C	14	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	45215	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	45201	> 99.9%
C	14	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	45215	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	45201	> 99.9%
C	14	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45215	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	45201	> 99.9%
C	14	< 0.1%

Tara
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1511
Distinct (%)	3.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15519.7983

Minimum	0
Maximum	50580
Zeros	160
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	0
5-th percentile	8220
Q1	14600
median	15140
Q3	15880
95-th percentile	19492
Maximum	50580
Range	50580
Interquartile range (IQR)	1280

Descriptive statistics

Standard deviation	4155.132945
Coefficient of variation (CV)	0.2677311177
Kurtosis	11.96684281
Mean	15519.7983
Median Absolute Deviation (MAD)	640
Skewness	1.985005454
Sum	701727680
Variance	17265129.79
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
15100	553	1.2%
14900	527	1.2%
14800	510	1.1%
15000	500	1.1%
15200	495	1.1%
15300	489	1.1%
14960	462	1.0%
14980	459	1.0%
15240	442	1.0%
15060	440	1.0%
Other values (1501)	40338	89.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	160	0.4%
1560	1	< 0.1%
1760	2	< 0.1%
1780	1	< 0.1%
1800	1	< 0.1%
1860	1	< 0.1%
1880	1	< 0.1%
2480	2	< 0.1%
2500	9	< 0.1%
2520	23	0.1%

Value	Count	Frequency (%)
50580	1	< 0.1%
49380	1	< 0.1%
48380	1	< 0.1%
47780	1	< 0.1%
47440	1	< 0.1%
47380	1	< 0.1%
47100	1	< 0.1%
47020	1	< 0.1%
47000	1	< 0.1%
46940	1	< 0.1%

bruto
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1432
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	43856.38947

Minimum	0
Maximum	128550
Zeros	160
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	0
5-th percentile	21650
Q1	44150
median	44850
Q3	45650
95-th percentile	50600
Maximum	128550
Range	128550
Interquartile range (IQR)	1500

Descriptive statistics

Standard deviation	10023.69258
Coefficient of variation (CV)	0.2285571771
Kurtosis	18.32910749
Mean	43856.38947
Median Absolute Deviation (MAD)	750
Skewness	1.196369788
Sum	1982966650
Variance	100474412.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
44750	993	2.2%
44850	963	2.1%
44650	957	2.1%
44800	950	2.1%
44700	935	2.1%
44950	914	2.0%
44600	893	2.0%
44500	893	2.0%
44550	880	1.9%
44900	870	1.9%
Other values (1422)	35967	79.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	160	0.4%
2550	1	< 0.1%
2750	1	< 0.1%
2800	1	< 0.1%
2850	1	< 0.1%
2900	1	< 0.1%
3250	1	< 0.1%
3300	1	< 0.1%
3900	1	< 0.1%
4400	1	< 0.1%

Value	Count	Frequency (%)
128550	1	< 0.1%
126500	1	< 0.1%
125650	1	< 0.1%
125100	1	< 0.1%
125050	2	< 0.1%
125000	1	< 0.1%
124900	1	< 0.1%
124800	1	< 0.1%
124400	2	< 0.1%
124250	1	< 0.1%

Liquido
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2408
Distinct (%)	5.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	28336.6938

Minimum	0
Maximum	103500
Zeros	164
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	0
5-th percentile	12050
Q1	29450
median	29760
Q3	30000
95-th percentile	34740
Maximum	103500
Range	103500
Interquartile range (IQR)	550

Descriptive statistics

Standard deviation	8480.345425
Coefficient of variation (CV)	0.2992708142
Kurtosis	17.71922392
Mean	28336.6938
Median Absolute Deviation (MAD)	270
Skewness	1.763006212
Sum	1281243610
Variance	71916258.53
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
29850	708	1.6%
29900	703	1.6%
29750	672	1.5%
29800	668	1.5%
29950	626	1.4%
29700	568	1.3%
29810	534	1.2%
29740	514	1.1%
29770	512	1.1%
29790	511	1.1%
Other values (2398)	39199	86.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	164	0.4%
500	1	< 0.1%
990	3	< 0.1%
1000	2	< 0.1%
1010	2	< 0.1%
1020	3	< 0.1%
1480	1	< 0.1%
1490	2	< 0.1%
1520	1	< 0.1%
1530	2	< 0.1%

Value	Count	Frequency (%)
103500	1	< 0.1%
100650	1	< 0.1%
99950	1	< 0.1%
99900	1	< 0.1%
99650	1	< 0.1%
99550	1	< 0.1%
99400	1	< 0.1%
99250	1	< 0.1%
98900	1	< 0.1%
98850	2	< 0.1%

qtdpedida
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	118
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	28778.48502

Minimum	500
Maximum	105000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	500
5-th percentile	13500
Q1	30000
median	30000
Q3	30000
95-th percentile	35000
Maximum	105000
Range	104500
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	8847.772134
Coefficient of variation (CV)	0.3074439856
Kurtosis	19.01030589
Mean	28778.48502
Median Absolute Deviation (MAD)	0
Skewness	2.312198234
Sum	1301219200
Variance	78283071.73
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
30000	33336	73.7%
15000	2753	6.1%
35000	2666	5.9%
10000	741	1.6%
25000	727	1.6%
12000	439	1.0%
20000	422	0.9%
5000	289	0.6%
25500	289	0.6%
9000	273	0.6%
Other values (108)	3280	7.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
500	1	< 0.1%
1000	10	< 0.1%
1500	7	< 0.1%
2000	16	< 0.1%
2500	8	< 0.1%
2800	3	< 0.1%
3000	70	0.2%
3500	5	< 0.1%
4000	38	0.1%
4500	7	< 0.1%

Value	Count	Frequency (%)
105000	1	< 0.1%
100000	46	0.1%
95000	3	< 0.1%
90000	94	0.2%
88000	2	< 0.1%
87000	2	< 0.1%
86000	9	< 0.1%
85000	144	0.3%
84000	17	< 0.1%
83000	15	< 0.1%

percDiff
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1432
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.003166968

Minimum	-3.08
Maximum	100
Zeros	760
Zeros (%)	1.7%
Negative	9691
Negative (%)	21.4%
Memory size	353.4 KiB

Quantile statistics

Minimum	-3.08
5-th percentile	-1.133333333
Q1	0.1
median	0.7
Q3	1.3
95-th percentile	2.25
Maximum	100
Range	103.08
Interquartile range (IQR)	1.2

Descriptive statistics

Standard deviation	6.054100686
Coefficient of variation (CV)	6.034988069
Kurtosis	256.3706532
Mean	1.003166968
Median Absolute Deviation (MAD)	0.6
Skewness	15.85313716
Sum	45358.19448
Variance	36.65213511
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	861	1.9%
0.3333333333	859	1.9%
0.6666666667	834	1.8%
0.5	807	1.8%
0	760	1.7%
0.8333333333	700	1.5%
0.6	677	1.5%
0.8	663	1.5%
0.4	652	1.4%
0.1666666667	645	1.4%
Other values (1422)	37757	83.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-3.08	1	< 0.1%
-3.071428571	1	< 0.1%
-3.066666667	8	< 0.1%
-3.055555556	1	< 0.1%
-3.035714286	1	< 0.1%
-3.033333333	5	< 0.1%
-3	28	0.1%
-2.966666667	4	< 0.1%
-2.96	1	< 0.1%
-2.959183673	1	< 0.1%

Value	Count	Frequency (%)
100	164	0.4%
2.904761905	1	< 0.1%
2.903225806	1	< 0.1%
2.901960784	1	< 0.1%
2.9	41	0.1%
2.896551724	1	< 0.1%
2.888888889	6	< 0.1%
2.885714286	3	< 0.1%
2.88	1	< 0.1%
2.875	3	< 0.1%

PostoOperacao
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	7
Distinct (%)	< 0.1%
Missing	16288
Missing (%)	36.0%
Memory size	353.4 KiB

SPEED2	5855
SPEED1	5432
PAL	5017
AUTOPAC	5008
PAL2	4056
Other values (2)	3559

Length

Max length	7
Median length	6
Mean length	5.126317973
Min length	3

Characters and Unicode

Total characters	148289
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	PAL
2nd row	SPEED1
3rd row	SPEED1
4th row	SPEED1
5th row	PAL

Common Values

Value	Count	Frequency (%)
SPEED2	5855	12.9%
SPEED1	5432	12.0%
PAL	5017	11.1%
AUTOPAC	5008	11.1%
PAL2	4056	9.0%
ENV2	1805	4.0%
ENV3	1754	3.9%
(Missing)	16288	36.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
speed2	5855	20.2%
speed1	5432	18.8%
pal	5017	17.3%
autopac	5008	17.3%
pal2	4056	14.0%
env2	1805	6.2%
env3	1754	6.1%

Most occurring characters

Value	Count	Frequency (%)
E	26133	17.6%
P	25368	17.1%
A	19089	12.9%
2	11716	7.9%
S	11287	7.6%
D	11287	7.6%
L	9073	6.1%
1	5432	3.7%
U	5008	3.4%
T	5008	3.4%
Other values (5)	18888	12.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	129387	87.3%
Decimal Number	18902	12.7%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
E	26133	20.2%
P	25368	19.6%
A	19089	14.8%
S	11287	8.7%
D	11287	8.7%
L	9073	7.0%
U	5008	3.9%
T	5008	3.9%
O	5008	3.9%
C	5008	3.9%
Other values (2)	7118	5.5%

Decimal Number

Value	Count	Frequency (%)
2	11716	62.0%
1	5432	28.7%
3	1754	9.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	129387	87.3%
Common	18902	12.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
E	26133	20.2%
P	25368	19.6%
A	19089	14.8%
S	11287	8.7%
D	11287	8.7%
L	9073	7.0%
U	5008	3.9%
T	5008	3.9%
O	5008	3.9%
C	5008	3.9%
Other values (2)	7118	5.5%

Common

Value	Count	Frequency (%)
2	11716	62.0%
1	5432	28.7%
3	1754	9.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	148289	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
E	26133	17.6%
P	25368	17.1%
A	19089	12.9%
2	11716	7.9%
S	11287	7.6%
D	11287	7.6%
L	9073	6.1%
1	5432	3.7%
U	5008	3.4%
T	5008	3.4%
Other values (5)	18888	12.7%

DataCriacao
Date

UNIQUE

Distinct	45215
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

Minimum	2019-11-29 10:30:00.977000
Maximum	2022-05-05 11:19:38.347000

Histogram

Histogram with fixed size bins (bins=50)

Dataentrada
Date

UNIQUE

Distinct	45215
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

Minimum	1900-01-01 00:00:00
Maximum	2022-05-05 11:20:56.543000

Histogram

Histogram with fixed size bins (bins=50)

TaraData
Date

MISSING

Distinct	18521
Distinct (%)	100.0%
Missing	26694
Missing (%)	59.0%
Memory size	353.4 KiB

Minimum	2019-11-30 11:44:20.763000
Maximum	2022-05-05 11:45:59.750000

Histogram

Histogram with fixed size bins (bins=50)

DataInicioOperacao
Date

MISSING

Distinct	18521
Distinct (%)	100.0%
Missing	26694
Missing (%)	59.0%
Memory size	353.4 KiB

Minimum	2019-11-30 11:44:20.763000
Maximum	2022-05-05 11:45:59.750000

Histogram

Histogram with fixed size bins (bins=50)

DataFimOperacao
Date

MISSING

Distinct	13693
Distinct (%)	100.0%
Missing	31522
Missing (%)	69.7%
Memory size	353.4 KiB

Minimum	2019-11-30 11:45:59.143000
Maximum	2022-05-05 12:32:08.247000

Histogram

Histogram with fixed size bins (bins=50)

BrutoData
Date

Distinct	45056
Distinct (%)	99.6%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

Minimum	1900-01-01 00:00:00
Maximum	2022-05-05 12:36:19.060000

Histogram

Histogram with fixed size bins (bins=50)

DataFecho
Date

Distinct	45212
Distinct (%)	> 99.9%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

Minimum	1900-01-01 00:00:00
Maximum	2022-05-05 12:36:21.450000

Histogram

Histogram with fixed size bins (bins=50)

Matricula
Categorical

HIGH CARDINALITY

Distinct	1822
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

117TU139	633
8277TU188	589
687TU166	568
6165TU183	489
6289TU143	463
Other values (1817)	42473

Length

Max length	10
Median length	9
Mean length	8.71206458
Min length	3

Characters and Unicode

Total characters	393916
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	658 ?
Unique (%)	1.5%

Sample

1st row	9400TU157
2nd row	7472TU203
3rd row	834TU182
4th row	5944TU137
5th row	7891TU183

Common Values

Value	Count	Frequency (%)
117TU139	633	1.4%
8277TU188	589	1.3%
687TU166	568	1.3%
6165TU183	489	1.1%
6289TU143	463	1.0%
9788TU123	443	1.0%
3133TU173	438	1.0%
4857TU106	422	0.9%
5567TU92	410	0.9%
3904TU216	409	0.9%
Other values (1812)	40351	89.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
117tu139	634	1.4%
8277tu188	589	1.3%
687tu166	568	1.3%
6165tu183	489	1.1%
6289tu143	463	1.0%
9788tu123	443	1.0%
3133tu173	438	1.0%
4857tu106	422	0.9%
5567tu92	410	0.9%
3904tu216	409	0.9%
Other values (1807)	40350	89.2%

Most occurring characters

Value	Count	Frequency (%)
1	56619	14.4%
T	44285	11.2%
U	44285	11.2%
2	33238	8.4%
8	29912	7.6%
7	28669	7.3%
3	28310	7.2%
9	27900	7.1%
6	26547	6.7%
5	25472	6.5%
Other values (6)	48679	12.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	305284	77.5%
Uppercase Letter	88622	22.5%
Lowercase Letter	10	< 0.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	56619	18.5%
2	33238	10.9%
8	29912	9.8%
7	28669	9.4%
3	28310	9.3%
9	27900	9.1%
6	26547	8.7%
5	25472	8.3%
0	24354	8.0%
4	24263	7.9%

Uppercase Letter

Value	Count	Frequency (%)
T	44285	50.0%
U	44285	50.0%
R	26	< 0.1%
S	26	< 0.1%

Lowercase Letter

Value	Count	Frequency (%)
t	5	50.0%
u	5	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	305284	77.5%
Latin	88632	22.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	56619	18.5%
2	33238	10.9%
8	29912	9.8%
7	28669	9.4%
3	28310	9.3%
9	27900	9.1%
6	26547	8.7%
5	25472	8.3%
0	24354	8.0%
4	24263	7.9%

Latin

Value	Count	Frequency (%)
T	44285	50.0%
U	44285	50.0%
R	26	< 0.1%
S	26	< 0.1%
t	5	< 0.1%
u	5	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	393916	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	56619	14.4%
T	44285	11.2%
U	44285	11.2%
2	33238	8.4%
8	29912	7.6%
7	28669	7.3%
3	28310	7.2%
9	27900	7.1%
6	26547	6.7%
5	25472	6.5%
Other values (6)	48679	12.4%

CodEntidade
Real number (ℝ_≥0)

Distinct	359
Distinct (%)	0.8%
Missing	9
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	398668.9294

Minimum	200482
Maximum	400589
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	200482
5-th percentile	400017
Q1	400046
median	400070
Q3	400125
95-th percentile	400373
Maximum	400589
Range	200107
Interquartile range (IQR)	79

Descriptive statistics

Standard deviation	11902.34801
Coefficient of variation (CV)	0.02985521852
Kurtosis	65.63598048
Mean	398668.9294
Median Absolute Deviation (MAD)	24
Skewness	-8.197186897
Sum	1.802222762 × 10¹⁰
Variance	141665888.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
400046	10592	23.4%
400093	5940	13.1%
400180	3228	7.1%
400030	1655	3.7%
400041	1276	2.8%
400059	1253	2.8%
400070	1094	2.4%
400044	975	2.2%
400091	922	2.0%
400187	791	1.7%
Other values (349)	17480	38.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
200482	1	< 0.1%
300173	21	< 0.1%
300179	1	< 0.1%
300181	9	< 0.1%
300182	3	< 0.1%
300183	1	< 0.1%
300185	4	< 0.1%
300187	26	0.1%
300188	2	< 0.1%
300190	2	< 0.1%

Value	Count	Frequency (%)
400589	3	< 0.1%
400588	6	< 0.1%
400587	2	< 0.1%
400586	2	< 0.1%
400585	3	< 0.1%
400584	31	0.1%
400583	4	< 0.1%
400494	5	< 0.1%
400490	2	< 0.1%
400488	1	< 0.1%

CodMotorista
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	262
Distinct (%)	2.6%
Missing	35326
Missing (%)	78.1%
Infinite	0
Infinite (%)	0.0%
Mean	9900004980

Minimum	9900000018
Maximum	9900010784
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.4 KiB

Quantile statistics

Minimum	9900000018
5-th percentile	9900000160
Q1	9900000984
median	9900006045
Q3	9900006892
95-th percentile	9900009452
Maximum	9900010784
Range	10766
Interquartile range (IQR)	5908

Descriptive statistics

Standard deviation	3137.19423
Coefficient of variation (CV)	3.168881467 × 10^-7
Kurtosis	-1.185618492
Mean	9900004980
Median Absolute Deviation (MAD)	1851
Skewness	-0.3739206895
Sum	9.790114924 × 10¹³
Variance	9841987.637
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9900000849	348	0.8%
9900007766	308	0.7%
9900006681	300	0.7%
9900000259	298	0.7%
9900009452	286	0.6%
9900003790	276	0.6%
9900000160	274	0.6%
9900006779	271	0.6%
9900000153	260	0.6%
9900006010	249	0.6%
Other values (252)	7019	15.5%
(Missing)	35326	78.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
9900000018	6	< 0.1%
9900000090	1	< 0.1%
9900000123	27	0.1%
9900000141	78	0.2%
9900000143	1	< 0.1%
9900000153	260	0.6%
9900000160	274	0.6%
9900000164	1	< 0.1%
9900000167	8	< 0.1%
9900000168	92	0.2%

Value	Count	Frequency (%)
9900010784	17	< 0.1%
9900010507	1	< 0.1%
9900010483	2	< 0.1%
9900010437	1	< 0.1%
9900010432	2	< 0.1%
9900010400	1	< 0.1%
9900010371	1	< 0.1%
9900010325	1	< 0.1%
9900010215	1	< 0.1%
9900010166	1	< 0.1%

NomeMotorista
Categorical

HIGH CARDINALITY

Distinct	2695
Distinct (%)	6.0%
Missing	0
Missing (%)	0.0%
Memory size	353.4 KiB

AID NSAIBIA	474
CHOKRI BEN FRADJ	429
NOOMEN SAIDI	391
NOUREDINE SAIDI	369
LOTFI FARHANI	367
Other values (2690)	43185

Length

Max length	33
Median length	25
Mean length	13.97162446
Min length	1

Characters and Unicode

Total characters	631727
Distinct characters	59
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	950 ?
Unique (%)	2.1%

Sample

1st row	HICHEM HAMMAMI
2nd row	AHMED MESSAI
3rd row	anouer jerou
4th row	HAZEM MESSOUDI
5th row	ZIED BEN TRAKI

Common Values

Value	Count	Frequency (%)
AID NSAIBIA	474	1.0%
CHOKRI BEN FRADJ	429	0.9%
NOOMEN SAIDI	391	0.9%
NOUREDINE SAIDI	369	0.8%
LOTFI FARHANI	367	0.8%
MOHAMED AYMEN BEN MANSOUR	361	0.8%
maher dhif	338	0.7%
HAYDER FARHAT	322	0.7%
adel ben amara	322	0.7%
anis hammami	317	0.7%
Other values (2685)	41525	91.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ben	4953	5.0%
mohamed	4302	4.3%
ali	1683	1.7%
ahmed	1214	1.2%
aymen	1150	1.2%
maher	1113	1.1%
hayder	1030	1.0%
mourad	1022	1.0%
lotfi	934	0.9%
saidi	904	0.9%
Other values (1996)	80983	81.6%

Most occurring characters

Value	Count	Frequency (%)
A	80733	12.8%
	54091	8.6%
I	53799	8.5%
E	44386	7.0%
M	35927	5.7%
H	34528	5.5%
D	28819	4.6%
R	28647	4.5%
N	22523	3.6%
L	22453	3.6%
Other values (49)	225821	35.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	487373	77.1%
Lowercase Letter	89615	14.2%
Space Separator	54091	8.6%
Dash Punctuation	453	0.1%
Other Punctuation	186	< 0.1%
Decimal Number	8	< 0.1%
Math Symbol	1	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	80733	16.6%
I	53799	11.0%
E	44386	9.1%
M	35927	7.4%
H	34528	7.1%
D	28819	5.9%
R	28647	5.9%
N	22523	4.6%
L	22453	4.6%
B	21571	4.4%
Other values (14)	113987	23.4%

Lowercase Letter

Value	Count	Frequency (%)
a	15708	17.5%
i	8261	9.2%
e	7862	8.8%
m	7430	8.3%
h	7170	8.0%
d	6018	6.7%
r	5402	6.0%
o	4272	4.8%
l	3887	4.3%
b	3691	4.1%
Other values (13)	19914	22.2%

Decimal Number

Value	Count	Frequency (%)
7	2	25.0%
1	1	12.5%
4	1	12.5%
2	1	12.5%
0	1	12.5%
6	1	12.5%
9	1	12.5%

Other Punctuation

Value	Count	Frequency (%)
*	176	94.6%
.	10	5.4%

Space Separator

Value	Count	Frequency (%)
	54091	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	453	100.0%

Math Symbol

Value	Count	Frequency (%)
+	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	576988	91.3%
Common	54739	8.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	80733	14.0%
I	53799	9.3%
E	44386	7.7%
M	35927	6.2%
H	34528	6.0%
D	28819	5.0%
R	28647	5.0%
N	22523	3.9%
L	22453	3.9%
B	21571	3.7%
Other values (37)	203602	35.3%

Common

Value	Count	Frequency (%)
	54091	98.8%
-	453	0.8%
*	176	0.3%
.	10	< 0.1%
7	2	< 0.1%
+	1	< 0.1%
1	1	< 0.1%
4	1	< 0.1%
2	1	< 0.1%
0	1	< 0.1%
Other values (2)	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	631727	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	80733	12.8%
	54091	8.6%
I	53799	8.5%
E	44386	7.0%
M	35927	5.7%
H	34528	5.5%
D	28819	4.6%
R	28647	4.5%
N	22523	3.6%
L	22453	3.6%
Other values (49)	225821	35.7%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	TipoDoc	TipoViatura	CodProduto	DescProduto	estado	Tara	bruto	Liquido	qtdpedida	percDiff	PostoOperacao	DataCriacao	Dataentrada	TaraData	DataInicioOperacao	DataFimOperacao	BrutoData	DataFecho	Matricula	CodEntidade	CodMotorista	NomeMotorista
0	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	14250	29100	14850	15000	1.000000	PAL	2022-05-05 11:19:38.347	2022-05-05 11:20:56.543	2022-05-05 11:24:41.697	2022-05-05 11:24:41.697	2022-05-05 11:42:16.453	2022-05-05 11:51:28.497	2022-05-05 11:51:30.590	9400TU157	400494.0	NaN	HICHEM HAMMAMI
1	TP	Z002	5	CIMENT I 42,5 R SAC	F	15600	45750	30150	30000	-0.500000	SPEED1	2022-05-05 10:51:03.003	2022-05-05 10:53:34.447	2022-05-05 11:45:59.750	2022-05-05 11:45:59.750	2022-05-05 12:32:08.247	2022-05-05 12:36:19.060	2022-05-05 12:36:21.450	7472TU203	400396.0	9.900007e+09	AHMED MESSAI
2	TP	Z002	5	CIMENT I 42,5 R SAC	F	14800	45000	30200	30000	-0.666667	SPEED1	2022-05-05 10:26:27.250	2022-05-05 10:29:35.117	2022-05-05 10:55:50.420	2022-05-05 10:55:50.420	2022-05-05 11:44:29.167	2022-05-05 12:09:31.900	2022-05-05 12:09:37.177	834TU182	400376.0	NaN	anouer jerou
3	TP	Z002	5	CIMENT I 42,5 R SAC	F	14800	44850	30050	30000	-0.166667	SPEED1	2022-05-05 10:07:39.820	2022-05-05 10:09:34.763	2022-05-05 10:20:37.433	2022-05-05 10:20:37.433	NaT	2022-05-05 10:54:07.287	2022-05-05 10:54:11.187	5944TU137	400588.0	NaN	HAZEM MESSOUDI
4	TP	Z004	42	CIMENT I 42,5 R SR3 PALETTE	F	7450	17300	9850	10000	1.500000	PAL	2022-05-05 10:00:56.097	2022-05-05 10:04:45.923	2022-05-05 10:22:43.433	2022-05-05 10:22:43.433	2022-05-05 10:28:07.907	2022-05-05 10:31:45.010	2022-05-05 10:31:50.837	7891TU183	400401.0	NaN	ZIED BEN TRAKI
5	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	2950	7900	4950	5000	1.000000	PAL2	2022-05-05 09:36:07.237	2022-05-05 09:42:17.633	2022-05-05 09:43:52.837	2022-05-05 09:43:52.837	NaT	2022-05-05 10:16:14.480	2022-05-05 10:16:20.120	1718TU112	400086.0	NaN	FETHI BOUSSAHA
6	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	15250	45000	29750	30000	0.833333	SPEED2	2022-05-05 09:35:14.067	2022-05-05 09:42:56.587	2022-05-05 10:06:20.490	2022-05-05 10:06:20.490	2022-05-05 10:56:51.007	2022-05-05 11:00:19.073	2022-05-05 11:00:25.933	319TU113	400086.0	NaN	NABIL BEN MBAREK
7	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	15650	45500	29850	30000	0.500000	AUTOPAC	2022-05-05 09:34:20.753	2022-05-05 09:36:19.813	2022-05-05 10:18:41.527	2022-05-05 10:18:41.527	2022-05-05 10:55:56.220	2022-05-05 10:58:23.180	2022-05-05 10:58:28.350	8170TU152	400046.0	NaN	AYMEN RHIMI
8	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	15000	44800	29800	30000	0.666667	AUTOPAC	2022-05-05 09:31:04.657	2022-05-05 09:32:15.940	2022-05-05 09:37:30.250	2022-05-05 09:37:30.250	2022-05-05 10:17:48.933	2022-05-05 10:21:26.287	2022-05-05 10:21:31.810	3513TU89	400046.0	NaN	MOHAMED TRABELSI
9	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	7250	17150	9900	10000	1.000000	SPEED2	2022-05-05 08:06:41.350	2022-05-05 08:07:31.770	2022-05-05 08:10:47.133	2022-05-05 08:10:47.133	2022-05-05 08:57:19.607	2022-05-05 08:58:25.923	2022-05-05 08:58:31.920	1338TU219	400046.0	NaN	KARIM BEN OUDA

Last rows

	TipoDoc	TipoViatura	CodProduto	DescProduto	estado	Tara	bruto	Liquido	qtdpedida	percDiff	PostoOperacao	DataCriacao	Dataentrada	TaraData	DataInicioOperacao	DataFimOperacao	BrutoData	DataFecho	Matricula	CodEntidade	CodMotorista	NomeMotorista
45205	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	14660	44600	29940	30000	0.200000	NaN	2019-11-29 17:15:14.713	2019-11-29 17:15:47.017	NaT	NaT	NaT	2019-11-29 17:49:48.943	2019-11-29 17:49:52.023	7952TU75	300214.0	NaN	IMED BEN ARFA
45206	TP	Z002	5	CIMENT I 42,5 R SAC	F	9100	28950	19850	20000	0.750000	NaN	2019-11-29 17:06:24.993	2019-11-29 17:07:13.823	NaT	NaT	NaT	2019-11-29 18:46:56.293	2019-11-29 18:47:03.213	3264TU117	300263.0	NaN	IBRAHIM MANAI
45207	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	14940	44650	29710	30000	0.966667	NaN	2019-11-29 16:29:25.210	2019-11-29 16:30:03.210	NaT	NaT	NaT	2019-11-29 18:25:15.680	2019-11-29 18:25:18.627	4852TU136	300350.0	NaN	HOSNI AHMED
45208	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	15080	44700	29620	30000	1.266667	NaN	2019-11-29 16:17:19.667	2019-11-29 16:17:54.060	NaT	NaT	NaT	2019-11-29 17:24:38.260	2019-11-29 17:24:40.710	2423TU162	300350.0	NaN	WALID DHIFAWI
45209	TP	Z002	5	CIMENT I 42,5 R SAC	F	15780	45400	29620	30000	1.266667	NaN	2019-11-29 16:11:41.073	2019-11-29 16:12:41.897	NaT	NaT	NaT	2019-11-29 17:17:25.290	2019-11-29 17:17:27.660	2168TU154	300330.0	NaN	ABDESSALEM KERANI
45210	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	14840	44550	29710	30000	0.966667	NaN	2019-11-29 16:08:01.580	2019-11-29 16:08:42.433	NaT	NaT	NaT	2019-11-29 17:22:10.140	2019-11-29 17:22:12.367	1425TU163	300348.0	NaN	MAJDI KHALIFI
45211	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	15540	45250	29710	30000	0.966667	NaN	2019-11-29 16:03:04.663	2019-11-29 16:04:01.157	NaT	NaT	NaT	2019-11-29 16:58:42.220	2019-11-29 16:58:44.587	8986TU212	300271.0	NaN	CHAABAN HAJRI
45212	TP	Z002	2	CIMENT II/AL 32,5 R SAC	F	15420	45250	29830	30000	0.566667	NaN	2019-11-29 15:49:36.817	2019-11-29 15:50:29.987	NaT	NaT	NaT	2019-11-29 16:50:01.820	2019-11-29 16:50:04.760	6774TU135	300386.0	NaN	MOHAMED RAHALI
45213	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	14480	44400	29920	30000	0.266667	NaN	2019-11-29 10:41:38.277	2019-11-29 10:43:05.387	NaT	NaT	NaT	2019-11-29 12:20:35.480	2019-11-29 12:20:42.660	5820TU130	300319.0	NaN	SABER HAFNAOUI
45214	TP	Z004	3	CIMENT II/AL 32,5 R PALETTE	F	15000	44650	29650	30000	1.166667	NaN	2019-11-29 10:30:00.977	2019-11-29 10:33:13.603	NaT	NaT	NaT	2019-11-29 11:20:30.497	2019-11-29 11:20:40.560	620TU112	300214.0	NaN	SALEM MIGHRI

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category